An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest
Abstract
In this study, we have assessed the validity and reliability of an automated labeling system that we have developed for subdividing the human cerebral cortex on magnetic resonance images into gyral based regions of interest (ROIs). Using a dataset of 40 MRI scans we manually identified 34 cortical ROIs in each of the individual hemispheres. This information was then encoded in the form of an atlas that was utilized to automatically label ROIs. To examine the validity, as well as the intra- and inter-rater reliability of the automated system, we used both intraclass correlation coefficients (ICC), and a new method known as mean distance maps, to assess the degree of mismatch between the manual and the automated sets of ROIs. When compared with the manual ROIs, the automated ROIs were highly accurate, with an average ICC of 0.835 across all of the ROIs, and a mean distance error of less than 1 mm. Intra- and inter-rater comparisons yielded little to no difference between the sets of ROIs. These findings suggest that the automated method we have developed for subdividing the human cerebral cortex into standard gyral-based neuroanatomical regions is both anatomically valid and reliable. This method may be useful for both morphometric and functional studies of the cerebral cortex as well as for clinical investigations aimed at tracking the evolution of disease-induced changes over time, including clinical trials in which MRI-based measures are used to examine response to treatment…
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The most popularly used cortical parcellation is the Freesurfer Desikan-Killiany cortical parcellation, while many other cortical parcellation schemes have also been widely used.
“The most popularly used cortical parcellation is the Freesurfer Desikan-Killiany cortical parcellation (Desikan et al., 2006; Fischl, 2012), while many other cortical parcellation schemes have also been widely used (Destrieux et al., 2010; Shattuck et al., 2008; Tzourio-Mazoyer et al., 2002).”
From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as Desikan et al., 2006
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- Authors
- Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., Buckner, R. L., Dale, A. M., Maguire, R. P., Hyman, B. T., Albert, M. S., & Killiany, R. J.
- Affiliations
- Boston University (US)
- MIT Computer Science and Artificial Intelligence Laboratory (US)
- Massachusetts General Hospital (US)
- Howard Hughes Medical Institute (US)
- University of California San Diego (US)
- Pfizer (United States) (US)
- Johns Hopkins University (US)
- Corresponding author
- Killiany, Ronald J.
- ORCID
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2006-07
- Volume
- 31
- Issue
- 3
- Pages
- 968-980
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2101135654
- Cited by
- 13,324
- References
- 66
- Citations by year
- 2026: 1062 · 2025: 1406 · 2024: 1305 · 2023: 1215 · 2022: 1329 · 2021: 1207 · 2020: 1104 · 2019: 886 · 2018: 764 · 2017: 641 · 2016: 548 · 2015: 510 · 2014: 355 · 2013: 333 · 2012: 198
- FWCI
- 61.04
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute on Aging (P01-AG04953)
- National Center for Research Resources (R01 RR 16594-01A1, P41-RR14075, BIRN002, U24 RR021382)
- National Institute of Biomedical Imaging and Bioengineering (R01 EB001550)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- human cerebral cortex, cortical parcellation, brain atlas, inter-rater reliability, intraclass correlation coefficient, morphometrics, treatment response monitoring
- MeSH terms
- Adult, Aged, Aged, 80 and over, Aging, Algorithms, Alzheimer Disease, Atrophy, Brain Mapping, Cerebral Cortex, Corpus Callosum, Dominance, Cerebral, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Software, Statistics as Topic, Reproducibility of Results, Observer Variation, Imaging, Three-Dimensional
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